The Integrated Household Panel Survey (IHPS) was integrated into the core Integrated Household Survey (IHS) program to study trends in poverty, socioeconomic and agricultural characteristics over time through a longitudinal survey.
At the time of the Third Integrated Household Survey (IHS3) 2010 (i.e. baseline), the IHPS sample (known as the IHPS 2010) had been selected, out of the overall IHS3 cross-sectional sample, to be representative at the national-, regional-, urban/rural levels, and for each of the following 6 strata: (i) Northern Region – Rural, (ii) Northern Region – Urban, (iii) Central Region – Rural, (iv) Central Region – Urban, (v) Southern Region – Rural, and (vi) Southern Region – Urban.
The IHPS 2013 attempted to track all baseline households as well as individuals that moved away from the baseline dwellings between 2010 and 2013 as long as they were neither servants nor guests at the time of the IHS3; were projected to be at least 12 years of age and were known to be residing in mainland Malawi but excluding those in Likoma Island and in institutions, including prisons, police compounds, and army barracks. Once a split-off individual was located, the new household that he/she formed/joined since 2010 was also brought into the IHPS sample. In view of the tracking rules, the final IHPS 2013 sample, therefore, included a total of 4,000 households that could be traced back to 3,104 baseline households.
Given the increasing numbers of households to be tracked, as well as budget/resource constraints, starting in 2016, the IHPS target household sample was adjusted as the households that have been associated with 102 out of 204 baseline EAs. Although the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS 2010 sample by region, urban and rural strata was still maintained with a proportional allocation of the sample across the regions, based on the distribution of the sampling frame from the 2008 Malawi Census. The selection ensured that the IHPS 2016 had a sufficient sample size in the urban stratum to obtain reliable national estimates for the urban and rural domains. Thus, starting in 2016, the IHPS domains of analysis will be limited to the national, urban and rural areas. The IHPS 2019 followed all individuals from the 2016 households.
The 2016 Integrated Household Panel Survey (IHPS) was launched in April 2016 as part of the Malawi Fourth Integrated Household Survey fieldwork operation. The IHPS 2016 targeted 1,989 households that were interviewed in the IHPS 2013 and that could be traced back to half of the 204 enumeration areas that were originally sampled as part of the Third Integrated Household Survey (IHS3) 2010/11. The 2019 IHPS was launched in April 2019 as part of the Malawi Fifth Integrated Household Survey fieldwork operations targeting the 2,508 households that were interviewed in 2016. The panel sample expanded each wave through the tracking of split-off individuals and the new households that they formed. Available as part of this project is the IHPS 2019 data, the IHPS 2016 data as well as the rereleased IHPS 2010 & 2013 data including only the subsample of 102 EAs with updated panel weights. Additionally, the IHPS 2016 was the first survey that received complementary financial and technical support from the Living Standards Measurement Study – Plus (LSMS+) initiative, which has been established with grants from the Umbrella Facility for Gender Equality Trust Fund, the World Bank Trust Fund for Statistical Capacity Building, and the International Fund for Agricultural Development, and is implemented by the World Bank Living Standards Measurement Study (LSMS) team, in collaboration with the World Bank Gender Group and partner national statistical offices. The LSMS+ aims to improve the availability and quality of individual-disaggregated household survey data, and is, at start, a direct response to the World Bank IDA18 commitment to support 6 IDA countries in collecting intra-household, sex-disaggregated household survey data on 1) ownership of and rights to selected physical and financial assets, 2) work and employment, and 3) entrepreneurship – following international best practices in questionnaire design and minimizing the use of proxy respondents while collecting personal information. This dataset is included here.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Children under 5 years
- Consumption expenditure commodities/items
- Agricultural household/ Holder/ Crop
Version 06: Edited, anonymized dataset for licensed access.
Version 03 included the following two datasets have been added:
- Unit conversion factor for food items ("ihs_foodconversion_factor_2020.dta")
- Caloric unit conversion factor ("caloric_conversionfactor.dta")
Version 04 included the following additional datasets and documents:
- Seasonal crops conversion factor (“ihs_seasonalcropconversion_factor_2020.dta”)
- Permanent crops conversion factor (“ihs_treeconversion_factor_2020.dta”)
- Household geo-variables (“householdgeovariables_y4.dta”)
- Plot geo-variables (“plotgeovariables_y4.dta”)
- Household identification (2016) data - modified (“hh_mod_a_filt_16.dta”)
- Household identification (2019) data - modified (“hh_mod_a_filt_19.dta”)
- The 2019 IHPS BID documented has been updated
- A document that described IHPS 2019 geo-variables has been added
Version 05: The 2019 IHPS household geo-variables dataset has been updated.
Version 06: "hh_mod_o_19.dta" data has been updated.
The Integrated Household Panel Survey series covers the following topics:
- Household and Geographic Area Identification and Survey Information (data of interview, enumerator's and supervisors codes, etc.)
- Household Roster
- Time Use and Labor
- Food Consumption (over past one week)
- Food Security
- Non-food Expenditures - over past one week and one month
- Non-food Expenditures - over past three months
- Non-food Expenditures - over past 12 months
- Durable Goods
- Farm Implements, Machinery, and Structures
- Household Enterprises
- Children Living Elsewhere
- Other Income
- Gifts Given Out
- Social Safety Nets
- Subjective Assessment of Well-being
- Shocks and Coping Strategies
- Child Anthropometry
- Deaths in Household
- Garden Roster (both for rainy season and dry (dimba) season)
- Plot Roster (both for rainy season and dry (dimba) season)
- Garden Details (both for rainy season and dry (dimba) season)
- Plot Details (both for rainy season and dry (dimba) season)
- Coupon Use (rainy season)
- Other Inputs (both for rainy season and dry (dimba) season)
- Crops (both for rainy season and dry (dimba) season)
- Seeds (both for rainy season and dry (dimba) season)
- Sales/ Storage (both for rainy season and dry (dimba) season)
- Tree/ Permanent Crop Production (last 12 months)
- Tree/ Permanent Crop Sales/ Storage (last 12 months)
- Livestock Products
- Access to Extension Services
- Network Roster
- Fisheries Calendar
- Fisheries Labor (last high season and last low season)
- Fisheries Inputs (last high season and last low season)
- Fisheries Output (last high season and last low season)
- Fish Trading (last high season and last low season)
- Roster of Informants
- Basic Information
- Economic Activities
- Community Needs, Actions and Achievements
- Communal Resource Management
- Communal Organization
The IHPS 2016 and 2019 attempted to track all IHPS 2013 households stemming from 102 of the original 204 baseline panel enumeration areas as well as individuals that moved away from the 2013 dwellings between 2013 and 2016 as long as they were neither servants nor guests at the time of the IHPS 2013; were projected to be at least 12 years of age and were known to be residing in mainland Malawi but excluding those in Likoma Island and in institutions, including prisons, police compounds, and army barracks.
Producers and sponsors
National Statistical Office (NSO)
Ministry of Economic Planning and Development (MoEPD)
The World Bank
Government of Malawi
World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture project
WB LSMS-ISA project
A sub-sample of IHS3 2010 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS 2013) and (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection. At baseline, the IHPS sample was selected to be representative at the national, regional, urban/rural levels and for each of the following 6 strata: (i) Northern Region - Rural, (ii) Northern Region - Urban, (iii) Central Region - Rural, (iv) Central Region - Urban, (v) Southern Region - Rural, and (vi) Southern Region - Urban. The IHPS 2013 main fieldwork took place during the period of April-October 2013, with residual tracking operations in November-December 2013.
Given budget and resource constraints, for the IHPS 2016 the number of sample EAs in the panel was reduced to 102 out of the 204 EAs. As a result, the domains of analysis are limited to the national, urban and rural areas. Although the results of the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS by region, urban and rural strata was maintained. The IHPS 2019 tracked all individuals 12 years or older from the 2016 households.
2,508 households from IHPS 2016 were the tracking targets for IHPS 2019 with 12,250 total individuals and 8,995 eligible individuals. By the end of the 2019 tracking operation the panel sample grew to 3,178 households with 14,649 individuals. This represents an entire household shift, or a single person from a household splitting off and forming a new one. These 3,178 households stemmed from 2,368 of the 2016 households representing a household-level attrition rate of 5.6 percent.
At the individual level, the calculation of the attrition rate is as follows. Baseline households contained 12,250 individuals in 2016, of whom 153 died between 2016 and 2019. Out of the remaining 12,097 individuals and irrespective of the tracking rules that were in place, the IHPS 2016 accounted for 10,516 baseline individuals, representing an overall attrition rate of 13 percent at the individual level. If one focuses only the individuals that were tracking-eligible in accordance with the aforementioned tracking rules and that were alive in 2016, the IHPS accounted for 7,737 individuals out of 8,859 tracking-eligible individuals, representing an attrition rate of 13 percent at the individual level.
The longitudinal panel analysis involves using the data for all the sample panel households that had completed interviews in all four rounds of the Panel Survey (2010 baseline, 2013, 2016 and 2019). Therefore the weights were calculated for this set of matched sample households (both original panel and split) for all four rounds. The calculation of the weights is described in detail in the Basic Information Document. A reference document that describes a similar panel weighting methodology used for the Tanzania Panel Survey is "Weight Calculations for Panel Surveys with Sub-Sampling and Split-off Tracking" (World Bank Policy Working Paper 6373, Kristen Himelein, February 2013).
Dates of Data Collection
Data Collection Mode
Computer Assisted Personal Interview [capi]
The IHPS 2019 field operations were regularly monitored through visits to the field-based teams by the NSO IHPS 2019 Managers, the World Bank IHPS 2019 Resident Advisor, and the technical missions from the World Bank LSMS-ISA team. In addition, data transmitted from the field was regularly reviewed for completeness and quality by the NSO IHPS 2019 Managers with the assistance of the World Bank IHPS 2019 Resident Advisor. The incoming data was organized and regularly checked for completeness and quality at the national, district, team, and enumerator level. The issues that were found in instrument implementation, general quality, or other technical issues were reviewed, and the appropriate corrective action taken by the NSO IHPS 2019 Managers and technical support staff either through revised field notes, additional field visits, remote communication directly with the field supervisors and/or general Whatsapp/SMS messages relayed to all teams.
After the first quarter of fieldwork, field supervisors and assistants were recalled to the cities of the different regions (Mzuzu, Blantyre, Lilongwe and Zomba) to discuss observations and concerns by field supervisors and to address observed concerns in the data. In general, field-based teams demonstrated extremely high commitment to collecting high quality data and the successful completion of the IHPS 2019 survey with the assistance of the NSO IHPS 2019 Management team. In a few cases, however, failure to alleviate quality concerns through the above-mentioned methods and individual coaching efforts lead to the restructuring of select field teams and or the replacement of field-based staff.
Data Collection Notes
Training of Field Staff
Field staff for the IHPS 2019 and the IHS5 was selected after advertisements were placed in the national newspapers advertising posts for enumerators. Interviews were conducted to determine the most qualified candidates.
Training instruction was given to the field staff by the IHS5 Management Team with help from World Bank LSMS-ISA team members. The training consisted of classroom instruction on the contents of the questionnaire, concepts and definitions, interview techniques and methods, and field practices in performing actual interviews to ensure that Enumerators fully understood the questionnaire. Training instructions are detailed in the Enumerator and Field Supervisor’s Manuals.
At the end of the training session, trainees were assessed based on tests given during the training process and evaluations by the supervisory personnel. 72 candidates were selected to be Field Enumerators and 18 members of NSO staff were chosen to be supervisors.
Field Work Implementation
The IHPS 2019 fieldwork began in April 2019 at the same time as the full IHS5 cross-section. Each of the 18 field-based mobile teams consisting of 1 supervisor, 4 enumerators and 1 driver were assigned to cover specific districts and received cross-sectional and panel assignments associated with these districts. Prior to leaving headquarters for fieldwork, team leaders and NSO management sorted carefully through all tracking forms for panel households to be sure that split-off households from 2016 were assigned to the correct team.
The IHPS 2019 field based supervisors were responsible for managing the daily operations of their respective field based mobile team. Each team supervisor received enumeration assignment schedules throughout the fieldwork. Enumeration assignments were further accompanied by (1) enumeration area maps, (2) completed listing forms, (3) the list of selected as well as replacement households to be interviewed in each EA (4) the Survey Solutions assignments for the selected EA from headquarters.
Primary responsibilities included: (1) liaising with IHPS 2019 management on schedules, field operation status, equipment status and needs, and special issues, (2) planning daily field operation schedules including coverage and transportation, (3) liaising with local authorities before commencing interview activities, (3) making Survey Solutions questionnaire assignments on CAPI and syncing completed interviews with their Supervisor account (4) reviewing incoming questionnaires for completion and accuracy, (5) syncing reviewed questionnaires with the Headquarters account, (6) reviewing error reports from Headquarters generated through Stata checking system and assigning questionnaire reviews, and authorizing review/call back based on these reports, (7) administering community questionnaires within each enumeration area.
Field based mobile teams consisted of 4 enumerators to field household interviews over the course of the scheduled fieldwork. An enumerator’s major areas of responsibility were to accurately and completely administer the Household, Agriculture, and Fishery questionnaires. The enumerators were responsible for: (1) locating assigned households, (2) relaying the source and purpose of the survey and obtaining respondent permission to implement the interview, (3) implementing all pertinent questionnaire modules, (4) systematically obtaining anthropometric measures for qualified household members, (5) using GPS technology to mark and record household locations and take agricultural field measurements, and (6) participating in the review and correction of questionnaires.
Data Entry Platform
To ensure data quality and timely availability of data, the IHPS 2019 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHPS 2019, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo tablet computer that the NSO provided. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.
The IHPS 2019 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHPS 2019 Interviews were mainly collected in “sample” mode (assignments generated from headquarters) and a few in “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample. This hybrid approach was necessary to aid the tracking operations whereby an enumerator could quickly create a tracking assignment considering that they were mostly working in areas with poor network connection and hence could not quickly receive tracking cases from Headquarters.
The range and consistency checks built into the application was informed by the LSMS-ISA experience with the IHS3 2010/11, IHPS 2013 and IHPS 2016. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (the NSO management) assigned work to the supervisors based on their regions of coverage. The supervisors then made assignments to the enumerators linked to their supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHPS 2019 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to Stata for other consistency checks, data cleaning, and analysis.
The data cleaning process was done in several stages over the course of fieldwork and through preliminary analysis. The first stage of data cleaning was conducted in the field by the field-based field teams utilizing error messages generated by the Survey Solutions application when a response did not fit the rules for a particular question. For questions that flagged an error, the enumerators were expected to record a comment within the questionnaire to explain to their supervisor the reason for the error and confirming that they double checked the response with the respondent. The supervisors were expected to sync the enumerator tablets as frequently as possible to avoid having many questionnaires on the tablet, and to enable daily checks of questionnaires. Some supervisors preferred to review completed interviews on the tablets so they would review prior to syncing but still record the notes in the supervisor account and reject questionnaires accordingly. The second stage of data cleaning was also done in the field, and this resulted from the additional error reports generated in Stata, which were in turn sent to the field teams via email or DropBox. The field supervisors collected reports for their assignments and in coordination with the enumerators reviewed, investigated, and collected errors. Due to the quick turn-around in error reporting, it was possible to conduct call-backs while the team was still operating in the EA when required. Corrections to the data were entered in the rejected questionnaires and sent back to headquarters.
The data cleaning process was done in several stages over the course of the fieldwork and through preliminary analyses. The first stage was during the interview itself. Because CAPI software was used, as enumerators asked the questions and recorded information, error messages were provided immediately when the information recorded did not match previously defined rules for that variable. For example, if the education level for a 12 year old respondent was given as post graduate. The second stage occurred during the review of the questionnaire by the Field Supervisor. The Survey Solutions software allows errors to remain in the data if the enumerator does not make a correction. The enumerator can write a comment to explain why the data appears to be incorrect. For example, if the previously mentioned 12 year old was, in fact, a genius who had completed graduate studies. The next stage occurred when the data were transferred to headquarters where the NSO staff would again review the data for errors and verify the comments from the enumerators and supervisors regarding anomalies that remain.
Additional cleaning was performed after interviews were “Approved” where appropriate to resolve systematic errors and organize data modules for consistency and efficient use. Case by case cleaning was also performed during the preliminary analysis specifically pertaining to out of range and outlier variables.
All cleaning activities were conducted led by the NSO, and the World Bank LSMS-ISA team provided technical assistance.
National Statistical Office
Ministry of Economic Planning and Development (MoEPD))
LSMS Data Manager
The World Bank
In receiving these data it is recognized that the data are supplied for use within my organization, and I agree to the following stipulations as conditions for the use of the data:
1. The data are supplied solely for the use described in this form and will not be made available to other organizations or individuals. Other organizations or individuals may request the data directly.
2. Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:
Commissioner Mercy Kanyuka
National Statistical Office
P.O. Box 333
Tel: +265 (0) 1 524 377/111
Fax: +265 (0) 1 525 130
web site: http://www.nsomalawi.mw/
The World Bank
Development Economics Research Group
LSMS Database Administrator
1818 H Street, NW
Washington, DC 20433, USA
tel: (202) 473-9041
fax: (202) 522-1153
3. The researcher will refer to the Malawi IHPS 2010-2013-2016-2019 Survey as the source of the information in all publications, conference papers, and manuscripts. At the same time, the World Bank is not responsible for the estimations reported by the analyst(s).
4. Users will not use the location information to reveal the identity of survey respondents
5. Users will not publish results (map or other form) that would allow communities or individuals to be identified
6. Users who download the data may not pass the data to third parties.
7. The database cannot be used for commercial ends, nor can it be sold.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
DDI Document ID
Development Economics Data Group
The World Bank Group
Documentation of the DDI
Date of Metadata Production
DDI Document version
Version 06 (July 2023). One dataset (“hh_mod_o_19.dta”) has been updated, the rest of the documentation is identical Version 05.